Health condition detection and monitoring using artificial intelligence

Abstract

Detection and monitoring of health conditions that are accompanied by an injury site includes receiving, by one or more processors, an identifier associated with a patient and an associated first image, the first image corresponding to an injury in the injury site. The one or more processors analyze the associated first image using a machine learning model that includes an inference engine and a knowledge base. The machine learning model compares the associated first image against a patient data history and a tracking database. In response to a determination the injury site is associated with the health condition, the one or more processors generate a first result including sending a report containing the first result to a healthcare professional caring for the patient and display the first result informing the patient and healthcare professional the injury needs special care including requiring an appointment.

What is claimed is: 
     
         1 . A computer-implemented method for detecting and monitoring a health condition accompanied by an injury site, comprising:
 receiving, by one or more processors, an identifier associated with a patient and an associated first image, the first image corresponding to an injury in the injury site in the patient's body;   analyzing, by the one or more processors, the associated first image using a machine learning model comprising an inference engine and a knowledge base, the machine learning model compares the associated first image against a patient data history and a tracking database;   in response to a determination the injury site is associated with the health condition, generating, by the one or more processors, a first result including sending a report containing the first result to a healthcare professional caring for the patient; and   displaying, by the one or more processors, the first result informing the patient and healthcare professional the injury site needs special care including requiring an appointment.   
     
     
         2 . The method of  claim 1 , wherein the health condition comprises a diabetic foot and the patient data history comprises type of diabetes, blood glucose result, glycated hemoglobin result, and patient generated health data including daily blood glucose measurements, calories ingested, mood, and an amount of physical exercises done. 
     
     
         3 . The method of  claim 1 , further comprising:
 in response to a determination the injury site is not associated with the health condition, generating, by the one or more processors, a second result as a probability the injury site is associated with the health condition.   
     
     
         4 . The method of  claim 3 , further comprising:
 storing, by the one or more processors, the second result including the identifier associated with the patient, a date and time of the associated first image, the associated first image, and a report of an analysis in the tracking database.   
     
     
         5 . The method of  claim 3 , further comprising:
 in response to the second result displaying a normal result, generating, by the one or more processors, an alert comprising a reminder for the patient to maintain blood work levels associated with the health condition within a normal range.   
     
     
         6 . The method of  claim 1 , further comprising:
 prompting, by the one or more processors, the patient to take a second image of the injury site in a next day for tracking and evaluation;   in response to receiving the second image of the injury site, comparing, by the one or more processors, the second image with the associated first image using the machine learning model to determine whether a change occurred including whether the injury site is associated with the health condition; and   in response to a determination the injury site is not associated with the health condition while the second image includes changes, generating, by the one or more processors, a third result as a probability the injury site is associated with the health condition.   
     
     
         7 . The method of  claim 6 , further comprising:
 storing, by the one or more processors, the third result including updated clinical data of the patient and updated patient generated health data in the tracking database;   in response to the third result, displaying, by the one or more processors, a normal result comprising a current treatment and a reminder to maintain normal blood work levels; and   in response to a determination the wound is treated successfully, displaying, by the one or more processors, a health condition prevention result informing the patient and healthcare professional of a successful treatment including importance of maintaining normal blood work levels and returning for a medical appointment on a scheduled date.   
     
     
         8 . A computer system for detecting and monitoring a health condition accompanied by an injury site, comprising:
 one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising:   
       receiving, by one or more processors, an identifier associated with a patient and an associated first image, the first image corresponding to an injury in the injury site in the patient's body;
 analyzing, by the one or more processors, the associated first image using a machine learning model comprising an inference engine and a knowledge base, the machine learning model compares the associated first image against a patient data history and a tracking database; 
 in response to a determination the injury site is associated with the health condition, generating, by the one or more processors, a first result including sending a report containing the first result to a healthcare professional caring for the patient; and 
 displaying, by the one or more processors, the first result informing the patient and healthcare professional the injury site needs special care including requiring an appointment. 
 
     
     
         9 . The computer system of  claim 8 , wherein the health condition comprises a diabetic foot and the patient data history comprises type of diabetes, blood glucose result, glycated hemoglobin result, and patient generated health data including daily blood glucose measurements, calories ingested, mood, and an amount of physical exercises done. 
     
     
         10 . The computer system of  claim 8 , further comprising:
 in response to a determination the injury site is not associated with the health condition, generating, by the one or more processors, a second result as a probability the injury site is associated with the health condition.   
     
     
         11 . The computer system of  claim 10 , further comprising:
 storing, by the one or more processors, the second result including the identifier associated with the patient, a date and time of the associated first image, the associated first image, and a report of an analysis in the tracking database.   
     
     
         12 . The computer system of  claim 10 , further comprising:
 in response to the second result displaying a normal result, generating, by the one or more processors, an alert comprising a reminder for the patient to maintain blood work levels associated with the health condition within a normal range.   
     
     
         13 . The computer system of  claim 8 , further comprising:
 prompting, by the one or more processors, the patient to take a second image of the injury site in a next day for tracking and evaluation;   in response to receiving the second image of the injury site, comparing, by the one or more processors, the second image with the associated first image using the machine learning model to determine whether a change occurred including whether the injury site is associated with the health condition; and   in response to a determination the injury site is not associated with the health condition while the second image includes changes, generating, by the one or more processors, a third result as a probability the injury site is associated with the health condition.   
     
     
         14 . The computer system of  claim 13 , further comprising:
 storing, by the one or more processors, the third result including updated clinical data of the patient and updated patient generated health data in the tracking database;   in response to the third result, displaying, by the one or more processors, a normal result comprising a current treatment and a reminder to maintain normal blood work levels; and   in response to a determination the wound is treated successfully, displaying, by the one or more processors, a health condition prevention result informing the patient and healthcare professional of a successful treatment including importance of maintaining normal blood work levels and returning for a medical appointment on a scheduled date.   
     
     
         15 . A computer program product for a health condition accompanied by an injury site, comprising:
 one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions comprising:   program instructions to receive, by one or more processors, an identifier associated with a patient and an associated first image, the first image corresponding to an injury in the injury site in the patient's body;   program instructions to analyze, by the one or more processors, the associated first image using a machine learning model comprising an inference engine and a knowledge base, the machine learning model compares the associated first image against a patient data history and a tracking database;   in response to a determination the injury site is associated with the health condition, program instructions to generate, by the one or more processors, a first result including sending a report containing the first result to a healthcare professional caring for the patient; and   program instructions to display, by the one or more processors, the first result informing the patient and healthcare professional the injury site needs special care including requiring an appointment.   
     
     
         16 . The computer program product of  claim 15 , wherein the health condition comprises a diabetic foot and the patient data history comprises type of diabetes, blood glucose result, glycated hemoglobin result, and patient generated health data including daily blood glucose measurements, calories ingested, mood, and an amount of physical exercises done. 
     
     
         17 . The computer program product of  claim 15 , further comprising:
 in response to a determination the injury site is not associated with the health condition, program instructions to generate, by the one or more processors, a second result as a probability the injury site is associated with the health condition.   
     
     
         18 . The computer program product of  claim 17 , further comprising:
 program instructions to store, by the one or more processors, the second result including the identifier associated with the patient, a date and time of the associated first image, the associated first image, and a report of an analysis in the tracking database.   
     
     
         19 . The computer program product of  claim 17 , further comprising:
 in response to the second result displaying a normal result, program instructions to generate, by the one or more processors, an alert comprising a reminder for the patient to maintain blood work levels associated with the health condition within a normal range.   
     
     
         20 . The computer program product of  claim 15 , further comprising:
 program instructions to prompt, by the one or more processors, the patient to take a second image of the injury site in a next day for tracking and evaluation;   in response to receiving the second image of the injury site, program instructions to compare, by the one or more processors, the second image with the associated first image using the machine learning model to determine whether a change occurred including whether the injury site is associated with the health condition;   in response to a determination the injury site is not associated with the health condition while the second image includes changes, program instructions to generate, by the one or more processors, a third result as a probability the injury site is associated with the health condition;   program instructions to store, by the one or more processors, the third result including updated clinical data of the patient and updated patient generated health data in the tracking database;   in response to the third result, program instructions to display, by the one or more processors, a normal result comprising a current treatment and a reminder to maintain normal blood work levels; and   in response to a determination the wound is treated successfully, program instructions to display, by the one or more processors, a health condition prevention result informing the patient and healthcare professional of a successful treatment including importance of maintaining normal blood work levels and returning for a medical appointment on a scheduled date.